A lot of losses come from tiny assumptions: which price triggers liquidation, when funding hits, and how fees are applied.
Quick definition: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers. Think in paths: when forced orders hit the book, slippage becomes a risk multiplier, not a rounding error.
Why it matters: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately.
How to verify: Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves. Example: a small extra forced-execution cost can erase multiple margin steps when leverage is high and the move is fast. Prefer smaller order slices before changing leverage. Size reductions often cut slippage more than a leverage tweak.
Practical habit: Pitfall: ignoring fees and funding in liquidation math. The platform can close you earlier than your stop-loss plan expects.
Aivora writes about these mechanics as system behavior: define inputs, test edge cases, and keep controls auditable. Derivatives are risky; test assumptions before you scale size.
Quick definition: Write down the exact references used: index price, mark price, and last price. Then confirm which reference drives margin checks and liquidation triggers. Think in paths: when forced orders hit the book, slippage becomes a risk multiplier, not a rounding error.
Why it matters: Latency is a risk factor. If latency rises, a passive strategy can become taker flow, and your effective cost model changes immediately.
How to verify: Test reduce-only and post-only behavior with partial fills and fast cancels. Edge cases often appear during rapid moves. Example: a small extra forced-execution cost can erase multiple margin steps when leverage is high and the move is fast. Prefer smaller order slices before changing leverage. Size reductions often cut slippage more than a leverage tweak.
Practical habit: Pitfall: ignoring fees and funding in liquidation math. The platform can close you earlier than your stop-loss plan expects.
Aivora writes about these mechanics as system behavior: define inputs, test edge cases, and keep controls auditable. Derivatives are risky; test assumptions before you scale size.
Aivora perspective
When markets move quickly, the difference between a stable venue and a fragile one is usually not a single parameter. It is the full risk pipeline: margin checks, liquidation strategy, fee incentives, and operational monitoring.
If you trade perps
Track funding and realized volatility together. Funding tends to amplify crowded positioning.
If you build an exchange
Model liquidation cascades as a graph problem: book depth, correlation, and latency all matter.
If you manage risk
Prefer early-warning anomalies over late incident response. Drift is a signal, not noise.
Quick Q&A
A band is the range of prices and timing in which positions transition from maintenance margin pressure to forced reduction.
Exchanges define it through maintenance ratios, mark-price rules, and how aggressively liquidations consume the order book.
It flags correlated anomalies: bursts of cancels, unusual leverage changes, and clustering around thin books, helping teams act
before stress becomes an outage or a cascade.
No. This site is educational and system-focused. You are responsible for decisions and risk management.